First things first, Quality Data is the desired data status: By “quality data” –it means clean, organized, actionable data from which to extract relevant information and insight. To get this data, you must have deep domain expertise in the acquisition, collection, management and delivery of structured and unstructured data, and you are equipped to aid both in crafting a business’s content strategy and in executing against such plans. Here are a few more principles:
Quality data is like the Holy Grail, businesses all want to achieve it; but not sure if it’s very doable: Business operates in the real world, and the real world is muddy and chaotic. Organizations need tools that deal with muddy and chaotic data, not a focus on making the data adapt to somewhat weaker tools.
Quality data leading to quality decision: Technology obviously plays a significant role in the content practice, contextual understanding, and once you get good data, you want it delivered to the end-users, via data-feed, API, web or mobile application. Quality data means how to transform the clean data into the useful information, and deliver it to the right people at the right time and location in order to make the quality decisions as well.
Big Data, quality data, quality is not equal to perfect, but good enough data to transform into business information and insight for capturing the trend or optimizing customer experience. As it is also important to leverage data quality and cost/benefit analysis. Still, quality data is means to the end, the end is how to run a high quality, high performing and high mature organization.